How Does HFT Take Advantage of Trend-Volume Signals?

Trading volume is used often to validate trends in stock prices or, alternatively, to indicate trend reversals. However, some evidence has shown that this methodology has become less effective over time, potentially because of the impact of high-frequency traders (HTFs). For this reason, this article investigates the efficacy of using trend and volume to predict future returns on time scales relevant to high-frequency traders themselves. To explore this issue, this study uses NASDAQ limit order book data and follows existing methodologies to find that low volume tends to lead to trend reversal, whereas high volume shows little or no predictive ability. We conclude that high-volume or low-volume periods are different in terms of their informativeness, which demonstrates the interests of HFTs in providing liquidity in the absence of information arrival and trend-inducing orders and not providing liquidity when the probability of adverse selection is high (liquidity evacuation).

Authors

Institutions

Publication Details

Journal
The Journal of Investing
Published
2026-10-29
DOI
https://doi.org/10.3905/joi.2026.025
Primary Topic
Financial Markets and Investment Strategies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

How Does HFT Take Advantage of Trend-Volume Signals?

Shouhao Li, Ricky Cooper, Benjamin Van Vliet
The Journal of Investing
Financial Markets and Investment Strategies
article

How Does HFT Take Advantage of Trend-Volume Signals?

Shouhao Li, Ricky Cooper, Benjamin Van Vliet
article en

Abstract

Trading volume is used often to validate trends in stock prices or, alternatively, to indicate trend reversals. However, some evidence has shown that this methodology has become less effective over time, potentially because of the impact of high-frequency traders (HTFs). For this reason, this article investigates the efficacy of using trend and volume to predict future returns on time scales relevant to high-frequency traders themselves. To explore this issue, this study uses NASDAQ limit order book data and follows existing methodologies to find that low volume tends to lead to trend reversal, whereas high volume shows little or no predictive ability. We conclude that high-volume or low-volume periods are different in terms of their informativeness, which demonstrates the interests of HFTs in providing liquidity in the absence of information arrival and trend-inducing orders and not providing liquidity when the probability of adverse selection is high (liquidity evacuation).

The Journal of Investing
Illinois Institute of Technology (US), University of Chinese Academy of Social Sciences (CN)
Openalex Percentile: Top 9%
Financial Markets and Investment Strategies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon